Network Visualization System for Financial Crime Detection
In evidenza

Financial crimes represent a major problem of many governments and are often related to organized crimes like terrorism and narcotics trafficking. Money laundering and frauds are among the most common types of financial crimes. They are based on relevant volumes of financial transactions to conceal the identity, the source, or the destination of illegally gained money.

The amount of money laundered globally is thought to easily exceed 1 trillion annually. To face this problem, most governments have created special investigation agencies, called financial intelligence units (FIUs). Financial institutions, like banks, money service businesses, insurance agencies, casinos, must store all transactions executed by their customers in some kind of electronic archive and must report to FIUs about suspicious transactions. The main goal of FIUs is to collect and analyze suspicious transaction data to discover illegal activities, so to defend the integrity of worldwide financial markets and to prevent from organized crimes that can mine the homeland security.

In this real-world scenario, we have developed a new software system, VisFAN, for the visual analysis of financial activity networks. It supports the analyst with effective tools to discover financial crimes, such as money laundering and frauds. VisFAN allows either the analysis of data within the same financial institution (bank, money service businesses, insurance agency, etc.) or the analysis of suspicious transaction data collected from different financial subjects. It offers novel algorithms and interaction functionalities for the visual exploration of networked data, and is equipped with tools for social network analysis and for the automatic generation of reports. The system is currently in use at the Financial Intelligence Agency (AIF) of the San Marino Republic.